plot_countFilt: Count differences
In lucyleeow/CellProfileR: Analyse Cell Morphology Data Generated By CellProfiler

Description Usage Arguments Functions

View source: R/count_differences.R

Determine the differences in count values between images (rows) before and after Cell Profiler filtering or manual filtering of poor quality and present as dataframe or plot in the current graphics device.

plot_countFilt(df_raw)

df_countFilt(df_raw, n = 10)

calc_countsImageQC(df_raw, df_filtered)

plot_countImageQC(df_raw, df_filtered, CP_unfiltered = FALSE)

df_countImageQC(df_raw, df_filtered, n = 10, CP_unfiltered = FALSE)

`df_raw`	Dataframe of raw Cell Profiler data with no images (rows) removed. Each row should be 1 image NOT 1 well.
`n`	Number of rows (images), with the largest differences, to include in the output dataframe.
`df_filtered`	Dataframe of Cell Profiler data after filtering for poor quality images (rows). Again, each row should be 1 image NOT 1 well.
`CP_unfiltered`	Single logical indicating whether the differences (before and after image filtering) should be calculted and shown for the CP filtered column 'Count_Cells' or CP unfiltered column 'Count_Cells_unfiltered'.

plot_countFilt: Calculates the difference between 'Count_Cells_unfiltered' and 'Count_Cells' (Cell Profiler filtering) for each row (image) and creates a density plot of the differences for ALL plates.
df_countFilt: Calculates the difference between 'Count_Cells_unfiltered' and 'Count_Cells' (Cell Profiler filtering) for each row (image) and outputs a dataframe containing the 'n' rows (images) that have the largest differences. Plate, well and image number also shown in dataframe.
calc_countsImageQC: Calculates the per well total count before and after filtering for poor quality images, for BOTH the 'Count_Cells_unfiltered' and 'Count_Cells' column (CP unfiltered and filtered). Mostly for internal use but made available as well.
plot_countImageQC: Calculates the difference in total count per well before and after filtering for poor quality images (for either the 'Count_Cells_unfiltered' or 'Count_Cells' column) then plots density plot of the differences for EACH plate.
df_countImageQC: Calculates the difference in total count per well before and after filtering for poor quality images (for either the 'Count_Cells_unfiltered' or 'Count_Cells' column) then produces a dataframe containing the 'n' rows (wells) with the largest differences.